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Experimental quantum simulation of a topologically protected Hadamard gate via braiding Fibonacci anyons

The Innovation 2023年第5期4卷 41-46页

作者： Yu-ang Fan Yingcheng Li Yuting Hu Yishan Li Xinyue Long Hongfeng Liu Xiaodong Yang Xinfang Nie Jun Li Tao Xin Dawei Lu Yidun Wan Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southem University of Science and Technology Shenzhen 518055China State Key Laboratory of Surface Physics Department of PhysicsCenter for Field Theory and Particle Physicsand Institute for Nanoelectronic Devices and Quantum ComputingFudan UniversityShanghai 200433and Shanghai Qi Zhi InstituteShanghai 200030China School of Physics Hangzhou Normal UniversityHangzhou 311121China

Topological quantum computation(TQC)is one of the most striking architectures that can realize fault-tolerant quantum *** TQC,the logical space and the quantum gates are topologically protected,i.e.,robust against local *** topological protection,however,requires complicated lattice models and hard-to-manipulate dynamics;even the simplest system that can realize universal TQC-the Fibonacci anyon system—lacks a physical realization,let alone braiding the non-Abelian ***,we propose a disk model that can simulate the Fibonacci anyon system and construct the topologically protected logical spaces with the Fibonacci *** braiding the Fibonacci anyons,we can implement universal quantum gates on the logical *** disk model merely requires two physical qubits to realize three Fibonacci anyons at the *** 15 sequential braiding operations,we construct a topologically protected Hadamard gate,which is to date the least-resource requirement for *** showcase,we implement a topological Hadamard gate with two nuclear spin qubits,which reaches 97.18%fidelity by randomized *** further prove by experiment that the logical space and Hadamard gate are topologically protected:local disturbances due to thermal fluctuations result in a global phase *** a platform-independent proposal,our work is a proof of principle of TQC and paves the way toward fault-tolerant quantum computation.

关键词： Fibonacci Hadamard TQC

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Online Flexible Busy Time Scheduling on Heterogeneous Machines 32

Online Flexible Busy Time Scheduling on Heterogeneous Machin...

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32nd Annual European Symposium on Algorithms, ESA 2024

作者： Călinescu, Gruia Davies, Sami Khuller, Samir Zhang, Shirley Department of Computer Science Illinois Institute of Technology ChicagoIL United States Department of EECS The Simons Institute for the Theory of Computing UC Berkeley CA United States Computer Science Department Northwestern University EvanstonIL United States Computer Science Department Harvard University CambridgeMA United States

ISBN: (纸本)9783959773386

We study the online busy time scheduling model on heterogeneous machines. In our setting, jobs with uniform length arrive online with a deadline that becomes known to the algorithm at the job's arrival time. An algorithm has access to machines, each with different associated capacities and costs. The goal is to schedule jobs on machines by their deadline, so that the total cost incurred by the scheduling algorithm is minimized. While busy time scheduling has been well-studied, relatively little is known when machines are heterogeneous (i.e., have different costs and capacities), despite this natural theoretical generalization being the most practical model for clients using cloud computing services. We make significant progress in understanding this model by designing an 8-competitive algorithm for the problem on unit-length jobs and provide a lower bound of 2 on the competitive ratio. The lower bound is tight in the setting when jobs form non-nested intervals. Our 8-competitive algorithm generalizes to one with competitive ratio 8(2p − 1)/p © Gruia Călinescu, Sami Davies, Samir Khuller, and Shirley Zhang;licensed under Creative Commons License CC-BY 4.0.

关键词： Scheduling algorithms

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Effect of Nonunital Noise on Random-Circuit Sampling

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PRX quantum 2024年第3期5卷 030317-030317页

作者： Bill Fefferman Soumik Ghosh Michael Gullans Kohdai Kuroiwa Kunal Sharma Department of Computer Science Institute for Quantum Computing Ontario N2L 2Y5 Canada IBM Quantum

In this work, drawing inspiration from the type of noise present in real hardware, we study the output distribution of random quantum circuits under practical nonunital noise sources with constant noise rates. We show that even in the presence of unital sources such as the depolarizing channel, the distribution, under the combined noise channel, never resembles a maximally entropic distribution at any depth. To show this, we prove that the output distribution of such circuits never anticoncentrates—meaning that it is never too “flat”—regardless of the depth of the circuit. This is in stark contrast to the behavior of noiseless random quantum circuits or those with only unital noise, both of which anticoncentrate at sufficiently large depths. As a consequence, our results shows that the complexity of random-circuit sampling under realistic noise is still an open question, since anticoncentration is a critical property exploited by both state-of-the-art classical hardness and easiness results.

关键词： quantum computation

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Faster Sampling Algorithms for Polytopes with Small Treewidth

Faster Sampling Algorithms for Polytopes with Small Treewidt...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Ke, Yekun Li, Xiaoyu Song, Zhao Zhou, Tianyi University of Washington Department of Computer Science SeattleWA United States Stevens Institute of Technology Department of Computer Science HobokenNJ United States The Simons Institute for the Theory of Computing University of California Berkeley BerkeleyCA United States University of Southern California Department of Computer Science Los AngelesCA United States

ISBN: (纸本)9798350362480

Sampling is a fundamental problem in optimization, machine learning and theoretical computer science. A common region of interest for sampling is the polytope, which is defined by a set of linear inequalities. The algorithm that is sampling from polytopes usually requires heavy matrix algebra, including matrix multiplication, matrix inversion and matrix determinant. In this work, we show how to implement the heavy matrix algebra in the area of sampling in nearly linear time for the polytope that has small treewidth. In particular, given a polytope defined by a matrix A ∈ n×d with treewidth τ, we improve the running time of each iteration for three typical sampling algorithms for polytopes such as Dikin Walk, Soft-Threshold Dikin Walk and Vaidya Walk from O(nd2) to O(nτ2) by exploiting the small treewidth structures of the matrices. © 2024 IEEE.

关键词： Trees (mathematics)

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AutoSketch: Automatic Sketch-Oriented Compiler for Query-driven Network Telemetry 21

AutoSketch: Automatic Sketch-Oriented Compiler for Query-dri...

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21st USENIX Symposium on Networked Systems Design and Implementation, NSDI 2024

作者： Sun, Haifeng Huang, Qun Sun, Jinbo Wang, Wei Li, Jiaheng Li, Fuliang Bao, Yungang Yao, Xin Zhang, Gong National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University China Institute of Computing Technology CAS China Northeastern University China Huawei Theory Department

ISBN: (纸本)9781939133397

Recent network telemetry witnesses tremendous progress in two directions: query-driven telemetry that targets expressiveness as the primary goal, and sketch-based algorithms that address resource-accuracy trade-offs. In this paper, we propose AutoSketch that aims to integrate the advantages of both classes. In a nutshell, AutoSketch automatically compiles high-level operators into sketch instances that can be readily deployed with low resource usage and incur limited accuracy drop. However, there remains a gap between the expressiveness of high-level operators and the underlying realization of sketch algorithms. AutoSketch bridges this gap in three aspects. First, AutoSketch extends its interface derived from existing query-driven telemetry such that users can specify the desired telemetry accuracy. The specified accuracy intent will be utilized to guide the compiling procedure. Second, AutoSketch leverages various techniques, such as syntax analysis and performance estimation, to construct efficient sketch instances. Finally, AutoSketch automatically searches for the most suitable parameter configurations that fulfill the accuracy intent with minimum resource usage. Our experiments demonstrate that AutoSketch can achieve high expressiveness, high accuracy, and low resource usage compared to state-of-the-art telemetry solutions. © 2024 Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, NSDI 2024. All rights reserved.

关键词： Economic and social effects

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Recovering the original simplicity: succinct and deterministic quantum algorithm for the welded tree problem

arXiv

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arXiv 2023年

作者： Li, Guanzhong Li, Lvzhou Luo, Jingquan Institute of Quantum Computing and Computer Theory School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

This work revisits quantum algorithms for the well-known welded tree problem, proposing a very succinct quantum algorithm based on the simplest coined quantum walks. It simply iterates the naturally defined coined quantum walk operator for a predetermined time and finally measure, where the predetermined time can be efficiently computed on classical computers. Then, the algorithm returns the correct answer deterministically, and achieves exponential speedups over any classical algorithm. The significance of the results may be seen as follows. (i) Our algorithm is rather simple compared with the one in (Jeffery and Zur, STOC’2023), which not only breaks the stereotype that coined quantum walks can only achieve quadratic speedups over classical algorithms, but also demonstrates the power of the simplest quantum walk model. (ii) Our algorithm theoretically achieves zero-error, which is not possible with existing methods. Thus, it becomes one of the few examples that exhibit exponential separation between deterministic (exact) quantum and randomized query complexities, which may also change people’s perception that since quantum mechanics is inherently probabilistic, it impossible to have a deterministic quantum algorithm with exponential speedups for the weled tree problem. © 2023, CC BY.

关键词： Trees (mathematics)

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quantum frontiers in high energy physics

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science China(Physics,Mechanics & Astronomy) 2025年第6期Mechanics & Astronomy) .卷 53-75页

作者： Yaquan Fang Christina Gao Ying-Ying Li Jing Shu Yusheng Wu Hongxi Xing Bin Xu Lailin Xu Chen Zhou Institute of High Energy Physics Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Physics Southern University of Science and Technology Interdisciplinary Center for Theoretical Study University of Science and Technology of China Peng Huanwu Center for Fundamental Theory State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Center for High Energy Physics Peking University Beijing Laser Acceleration Innovation Center State Key Laboratory of Particle Detection and Electronics Department of Modern Physics University of Science and Technology of China Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum MatterSouth China Normal University Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing Center South China Normal University Southern Center for Nuclear-Science Theory Institute of Modern Physics Chinese Academy of Sciences

Numerous challenges persist in high energy physics(HEP), the addressing of which requires advancements in detection technology, computational methods, data analysis frameworks, and phenomenological designs. We provide a concise yet comprehensive overview of recent progress across these areas, in line with advances in quantum technology. We will discuss the potential of quantum devices in detecting subtle effects indicative of new physics BSM, the transformative role of quantum algorithms and large-scale quantum computers in studying real-time non-perturbative dynamics in the early universe and at colliders, as well as in analyzing complex HEP data. Additionally, we emphasize the importance of integrating quantum properties into HEP experiments to test quantum mechanics at unprecedented high-energy scales and search for hints of new physics. Looking ahead, the continued integration of resources to fully harness these evolving technologies will enhance our efforts to deepen our understanding of the fundamental laws of nature.

关键词： high energy physics quantum sensing quantum simulations quantum machine learning quantum information

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Boosting Meaningful Dependency Mining with Clustering and Covariance Analysis 40

Boosting Meaningful Dependency Mining with Clustering and Co...

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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Wang, Xi Jin, Ruochun Huang, Wanrong Tang, Yuhua Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China College of Computer Science and Technology Department of Intelligent Data Science National University of Defense Technology Changsha China

ISBN: (纸本)9798350317152

Functional dependencies (FDs) form a valuable ingredient for various data management tasks. However, existing methods can hardly discover practical and interpretable FDs, especially in large noisy real-life datasets. This paper studies the problem of discovering meaningful functional dependencies (FDms) that utilize support and error parameters to capture interesting dependencies in such datasets and proposes an efficient discovery algorithm called FDM?. In order to scale with large datasets, FDM ? employs an efficient sampling method with accuracy guarantees to capture the differences between tuple pairs and to quantify the connection between support/error of dependencies on samples and those on the entire dataset. Moreover, it adopts a clustering-based correlated attributes extraction to divide the exponentially large search space into multiple small sub-spaces and proposes an easy-first traversal strategy with covariance-based guidance that quickly detects candidate dependencies and validates them. Additionally, we prove a covariance lower bound as an additional pruning criterion to reduce the search space. Extensive experiments on real-life and synthetic datasets demonstrate that FDM ? is 14 times faster than existing discovery algorithms on average, up to 31 times, and scales to larger datasets with the least memory cost. © 2024 IEEE.

关键词： Large datasets

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PancakeFS: A Write Efficiently and Read Optimized Filesystem 4

PancakeFS: A Write Efficiently and Read Optimized Filesystem

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4th International Conference on Consumer Electronics and computer Engineering, ICCECE 2024

作者： Wang, Yongkang Liu, Yang Chen, Zhiguang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Institute for Quantum Information College of Computer National University of Defense Technology State Key Laboratory of High-Performance Computing Changsha China

ISBN: (纸本)9798350384062

With the development of emerging technologies such as cloud computing and large AI models (such as LLM), many applications have placed higher demands on the intensive read and write processing of massive data. Addressing the limitations of traditional file systems, we propose PancakeFS, an LSM-Tree-based file system. Leveraging the write-friendly characteristics of LSM-Tree, PancakeFS exhibits efficient write performance. We improve read performance through the design of an inode allocation algorithm based on subtree partitioning and optimization of the disk layout for hot data reconstruction. Our experimental results demonstrate that PancakeFS outperforms Ext4 and TableFS in terms of both read and write performance. © 2024 IEEE.

关键词： Data handling

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Self-distillation Enhanced Vertical Wavelet Spatial Attention for Person Re-identification 1

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Zhang, Yuxuan Tan, Huibin Lan, Long Teng, Xiao Ren, Jing Zhang, Yongjun Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Beijing100071 China

ISBN: (数字)9783031533082

ISBN: (纸本)9783031533075

Person re-identification is a challenging problem in computer vision, aiming to accurately match and recognize the same individual across different viewpoints and cameras. Due to significant variations in appearance under different scenes, person re-identification requires highly discriminative features. Wavelet features contain richer phase and amplitude information as well as rotational invariance, demonstrating good performance in various visual tasks. However, through our observations and validations, we have found that the vertical component within wavelet features exhibits stronger adaptability and discriminability in person re-identification. It better captures the body contour and detailed information of pedestrians, which is particularly helpful in distinguishing differences among individuals. Based on this observation, we propose a vertical wavelet spatial attention only with the vertical component in the high frequency specifically designed for feature extraction and matching in person re-identification. To enhance spatial semantic consistency and facilitate the transfer of knowledge between different layers of wavelet attention in the neural network, we introduce a self-distillation enhancement method to constrain shallow and deep spatial attention. Experimental results on Market-1501 and DukeMTMC-reID datasets validate the effectiveness of our model. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Distillation

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